Artificial intelligence will soon change how we conduct our daily lives. Are companies prepared to capture value from the oncoming wave of innovation?
Pity the radiology department at your local hospital. Yes, they have a fine MRI machine and powerful software to generate the images. But that’s where the machines bog down. The radiologist has to find and read the patient’s file, examine the images, and make a determination. What if artificial intelligence (AI) could jump-start that process by enabling real-time and more accurate diagnoses or guidance, beyond what human eyes can see?
Thanks to technological advances over the past few years, manufacturers are close to offering such leading-edge MRI solutions. In fact, they’re exploring new AI applications that span virtually every major industry, from industrials to the public sector. With better algorithms and increased stores of data, the error rate for computer calculations is now often similar to or better than those of human beings for image recognition and several other cognitive functions. Hardware performance has also improved drastically, allowing machines to process this unprecedented amount of data. That has been a major driver of the improvement in the accuracy of AI models.
Within AI, deep learning (DL) represents the area of greatest untapped potential. (For more information on AI categories, see sidebar, “The evolution of AI”). This technology relies on complex neural networks that process information using various architectures, comprised of layers and nodes, that approximate the functions of neurons in a brain. Each set of nodes in the network performs a different pattern analysis, allowing DL to deliver far more sophisticated insights than earlier AI tools. With this increased sophistication comes greater needs for leading-edge hardware and software.
Well aware of AI’s massive potential, leading high-tech companies have taken early steps to win in this market. But the industry is still nascent and a clear recipe for success hasn’t emerged. So how can companies capture value and see a return on their huge AI investments?
Our research, as well as interactions with end customers of AI, suggests that six tenets will ring true once the dust settles. First off, value capture will initially be limited in the consumer space, and companies will achieve most value by focusing on enterprise “microverticals”—specific use cases within select industries. Our analysis of the technology stack also suggests that opportunities will vary by layer and that the most successful companies will pursue end-to-end solutions, often through partnerships or acquisitions. For certain hardware players, AI might represent a reversal of fortune, after years of waning interest from investors who gravitated toward software, combined with heavy commoditization that depressed margins. We believe that the advent of AI opens significant opportunities, with solutions in both the cloud and the edge generating strong end-customer demand. But our most important takeaway is that companies need to act quickly. Those that make big bets now and overhaul their traditional strategies will emerge as the winners.
